System and method for revolving credit product offer customization

ABSTRACT

A system and method are disclosed for making an offer for at least one revolving credit product to an applicant. An identifier for each of a plurality of revolving credit products is stored and at least one attribute ( 145 ) is associated with each of the revolving credit products. An application for a revolving credit product is received from an applicant ( 105 ). One or more of the revolving credit product issuer&#39;s ( 160 ) objectives are identified. A set of revolving credit products that fit within an applicant profile is created, ranked, and at least one of the top ranking revolving credit products are then offered to the applicant from the set of revolving credit products.

RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.10/398,613 filed Apr. 7, 2003, which claims priority to PCT ApplicationNo. PCT/US01/31471, which claims priority from U.S. ProvisionalApplication No. 60/238,500 of Sulkowski et al. filed Oct. 6, 2000, eachof which is herein incorporated by reference in its entirety.

FIELD OF THE INVENTION

The present invention relates to a revolving credit product issuersystem for customization of revolving credit products and complementaryservice offers in response to customer and prospective-customer needs,credit risks, and anticipated behavior. One revolving credit product maybe, for example, a credit card with a single set of terms. Anotherrevolving credit product may be, for example a line of credit. In stillother' embodiments, the revolving credit product may be any combinationof revolving credit products.

BACKGROUND OF THE INVENTION

In existing revolving credit product issuing businesses, issuers maysend prospective customers offers through, for example, the mail. Whilerevolving credit product issuers attempt to customize their offers andservices to a customers' needs based upon known characteristics of apotential mailing group, such solicitations can not be customized toeach individual. Moreover, current revolving credit product systems donot provide the flexibility to permit customer interaction in theprocess.

In addition, existing computer systems used for maintaining existingcustomer revolving credit product accounts generally permit the creditlimit of customers with good credit history to be increased, and ofthose with risky credit history to be decreased. These systems, however,cannot automatically respond to customer's needs or learn theiranticipated behavior.

There is a need to make more personalized offers for revolving creditproduct and complementary services to prospective and current customers.

SUMMARY OF THE INVENTION

It is an object of the present invention to provide a revolving creditproduct issuer with a method and apparatus for interacting with currentand prospective customers, and thereby to provide targeted offers tosuch current and/or prospective customers.

It is a further object of the present invention to provide a revolvingcredit product issuer with a method and apparatus for managing arevolving credit product account portfolio that is determined based uponthe issuers internal objectives.

It is yet another object of the present invention to provide a systemand method for delivering targeted revolving credit product offers overthe Internet.

It is another object of the present invention to integrate external dataand data provided by potential consumers to indentify and electronicallydeliver credit product offerings for the potential consumer.

It is yet a further object of the present invention to providealternative, more suitable offerings to potential consumers that haverejected one or more previous credit product offerings.

To meet the need of providing a revolving credit product issuer with theability to make more personalized offers for revolving credit productsand complementary services to prospective and current customers, theinventive system positions a revolving credit product issuer so that itcan provide customized offers to both existing revolving credit productcustomers and to prospective customers. The system evaluates relevantexperience for revolving credit product users, directly aligns theissuer's strategic and marketing objectives with the users' experience,and learns quickly from web-based marketing experiences.

The objective of the present invention may be accomplished throughseveral modules. In one embodiment of the invention, the modules areincorporated into the revolving credit product issuer's Internetplatform. Together, these modules can enable the customization of offersthat issuers provide to an applicant. In one embodiment of theinvention, the modules comprise an: (1) Initial Input Module; (2)Applicant Characterization Module; (3) Product Offers Module; (4)Complementary Product Offers Module; (5) Offer Refinement Module; (6)Performance Tracking Module and (7) Learning Module. These seven modulescan customize the experiences for: (1) applicant's who currently do nothave a revolving credit product with the issuer and are seeking arevolving credit product, (2) applicants who have a credit product withthe issuer and are seeking another or a replacement revolving creditproduct, or (3) applicants who have a revolving credit product with theissuer and are seeking some modification to their revolving creditproduct.

In one embodiment, the present invention comprises: an initial inputmodule that selects and presents questions to an applicant and solicitsresponses from said applicant; an applicant characterization module thatcharacterizes applicants based on the responses to questions presentedby the initial input module; a product offers module that determines andpresents an ideal product offer to the applicant based on theapplicant's characterization and on the relative importance of theissuer's objectives; a complementary product offers module thatdetermines and presents an appropriate complementary product offer tothe applicant based on the applicant's characterization and on therelative importance of the issuer's objectives; an offer refinementmodule that, for applicants who have rejected offers presented by eitherthe product offers module or the complementary product offers module,identifies alternative offers acceptable to the issuer that more closelyalign with the applicant's needs than the rejected offers; a performancetracking module that generates reports summarizing applicant behaviorand the issuer's profitability and sales performance, based on questionspresented to a plurality of applicants, responses to those questions,product offers presented to the plurality of applicants, and rejectionsand acceptances of those product offers; and a learning module thatevaluates applicants' responses and behavior associated with acceptedand rejected product offers to improve future targeting offers toapplicants.

One embodiment of the present invention enables issuers to characterizeinternal objectives, focusing on the relative and absolute importance ofaccount growth, asset growth, risk management and profit management. Thepresent invention also enables issuers to integrate and leverageexternal data, such as credit bureau data, demographic data, etc., andvisit generated data, such as answers to questions, URLs, cookies, etc.,to profile each applicant in terms of product attributes they value,credit risk, anticipated behavior and current behavior (if currentcustomer).

Another embodiment of the present invention further enables issuers toidentify the best credit product offers and complementary product offersto make to each individual applicant in the context of the issuer'sobjectives. The invention enables issuers to identify what attributesthe applicant can change to refine the offer and refine and learn asexperience and data are gained. The invention can meet issuer's goalswhile responding to the applicant's needs, credit risk, and anticipatedbehavior.

The present invention is compatible with front-end and web-sitemanagement capabilities. The invention relies on a cross issuer databaseof customer behavior, risk and profitability. Such data are compiledlongitudinally and are supplemented with extensive primary marketresearch. The invention relies on the segmentations and account levelvaluation methods. The invention utilizes experience with behavior andprofitability modeling at the individual customer level.

A preferred embodiment of the method of the invention includes severalsteps. First, an identifier for each of a plurality of revolving creditproducts is stored. At least one attribute is associated with each ofthe revolving credit products.

An application is then received from the applicant. The application isprofiled based on certain characteristics to provide an applicantprofile. In one embodiment of the invention, the applicant profile mayinclude: (1) the value he/she ascribes to revolving credit products andcomplementary features; (2) credit risk; (3) anticipated credit productbehavior; and (4) current behavior with the issuer's credit products (ifhe/she is a current credit product customer).

The issuer's objectives of an offer are identified. In one embodiment ofthe invention, the revolving credit issuer defines the relativeimportance of its various business objectives. These objectives mayinclude account generation, asset generation, specific goals for riskmanagement and profit management.

A set of revolving credit products is created. The set may comprise aplurality of revolving credit products that fit within the applicant'sprofile. The revolving credit products in the set of revolving creditproducts are then ranked based upon the objective of the offer, and theattributes of the revolving credit products.

An offer is made to the applicant of at least one of the top rankingrevolving credit products from the set of revolving credit products.

Should an offer be rejected by an applicant, the revolving creditproduct issuer may make counter-offers to the applicant, and theapplicant may evaluate alternatives to the initial offer set. Thisoption is crafted so that the applicant can highlight credit productfeatures he or she wants to adjust so that credit product alternativesmore closely aligned to the applicant's needs can be identified. Thesealternatives are offered only if the revolving credit product issuer isstill able to meet its business objectives.

In addition, the invention incorporates applicants' feedback and learnsover time, improving targeted offers to applicants by focusing onresponse rate, risk, behavior and profitability.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a general overview of the modules and databases accordingto one embodiment of the present invention.

FIG. 2 depicts a flow chart describing a general overview of the methodaccording to one embodiment of the present invention.

FIG. 3 depicts a flowchart of the steps comprising the Initial ProductModule according to one embodiment of the present invention.

FIG. 4 depicts a flowchart of the steps comprising the ApplicantCharacterization Module according to one embodiment of the presentinvention.

FIG. 5 depicts a flowchart of the steps comprising the Product OffersModule according to one embodiment of the present invention.

FIG. 6 depicts a flowchart of the steps comprising the ComplementaryProduct Offers Module according to one embodiment of the presentinvention.

FIG. 7 depicts a flowchart of the steps comprising the Offer RefinementModule according to one embodiment of the present invention.

FIG. 8 depicts a flowchart of the steps comprising the PerformanceTracking Module according to one embodiment of the present invention.

FIG. 9 depicts a flowchart of the steps comprising the Learning Moduleaccording to one embodiment of the present invention.

DETAILED DESCRIPTION OF THE INVENTION

The present invention, an application system, relates to a system andmethod for making a customized offer for revolving credit products to anapplicant in response to the issuer's objectives for the offer and theapplicant's needs, credit risks, and anticipated behavior.

The term revolving credit product, as used herein is used in thebroadest sense of its ordinary meaning, namely, to refers to creditproducts that permit ongoing debits and credits to an account. Examplesof revolving credit products includes credit cards and credit lines.

In one embodiment of the invention, an applicant may be offered a choicebetween the one or more revolving credit products such as credit cards,each credit card having its own unique set of attributes, includingcredit terms. In another embodiment of the invention the applicant maybe offered a choice between one or more revolving credit products suchas various credit lines with differing attributes. In still a furtherembodiment of the invention, the applicant may be offered a choice ofrevolving credit product involving a combination of revolving creditproducts, and thus, include one or more credit cards, credit lines orother revolving credit products.

The present invention may be implemented in a computer program thatexecutes on a revolving credit product issuer's computer system, and isaccessible to applicants via a computer network such as the Internet.

An overview of the system components according to one embodiment of thepresent invention is shown in FIG. 1. In the embodiment of the inventionillustrated, seven modules are incorporated into a revolving creditproduct issuer's network platform to enable the customization of offersto individual prospective and/or active customers. As described above,in one embodiment of the invention, the network platform is theInternet. The modules are operatively connected to each other, and toseveral databases and/or system components as shown in FIG. 1 anddescribed herein.

The first system component an applicant to the issuer's site encountersis a screener 100. Screener 100 may be a hardware or software componentthat possesses “front end” or initial screening questions to theapplicant in an attempt to determine the applicant's demographicinformation, and reason for entering the issuer's site. The screener mayalso attempt to ascertain whether the applicant is a prospective,current, or former customer of the issuer.

Once the initial screening questions are answered, the applicant ispassed over to Initial Input Module (“IIM”) 105 i.e. Module 1. Thepurpose of IIM 105 is to clarify the characteristics of each applicant,and enables credit risk evaluation for those “thin-file” applicants thatwould not otherwise qualify for credit based on available credit bureaufiles. IIM 105 accomplishes this task by delivering meaningful questionsthat build on each other in order to clarify the characteristics of eachapplicant. (e.g., Are you a full-time student? If so, what is the nameand address of your university or college? Are you employed? If so, whatis the name and address of your company?).

Once the initial questions in IIM 105 are completed the applicant istransferred to an applicant Characterization Module (“ACM”) 110, i.e.Module 2. ACM 110 characterizes the applicant based on external data andapplicant responses to the questions presented in IIM 105. ACM 110 thenassigns the applicant to a pool that reflects their characteristics. Inone embodiment of the invention the applicants are characterizedaccording to four objectives: risk assessment; behavior pattern; valueassessment; and likelihood of acceptance.

In one embodiment of the invention, the risk assessment is in the formof a FICO score (Fair Isaacs and Company Credit Risk Score). The FICOscore may be obtained from a standard credit report.

The behavior pattern represents the behavior, and anticipated behaviorof an applicant with regard to revolving credit products. In oneembodiment of the invention, the behavior pattern is described as anumerical score and presented in the form of a vector. Some behaviorpatterns that factor into the behavior pattern score include: theapplicant's needs and requests regarding the revolving credit product;the applicant's past transactions regarding revolving credit product,and the potential profitability to the revolving credit product issuerbased on the applicant's transaction history; etc.

A third objective that may be used to describe or characterize anapplicant is a value assessment. In one embodiment of the invention,discrete choice questions are posed to the applicant (e.g., Do youprefer a credit card with an APR of 9.9% and no annual fee to a creditcard with an APR of 7.9% and an annual fee of $75?), and the responsesevaluated. The value assessment then assigns a value assessment tag tothe applicant based on the applicant's responses.

In one embodiment of the invention, the value assessment tag representsa score for the applicant relative to a segment or group of otherapplicants. These segments or groups may represent a category orclassification of other applicants with known similar characteristics.Some categories that may comprise the applicant groups includedescriptions of the applicant's needs and requests, and include:frequent flyer; low fees but higher monthly interest rates; desiresrewards points; etc.

Another objective that may be used to describe or characterize theapplicant is the likelihood of acceptance. In one embodiment of theinvention, the likelihood of acceptance can be predicted using theattributes of the revolving credit product and the applicant's values orvalue assessment (using conjoint analysis or discrete choice utilityfunctions, for example).

The ACM 110 is operatively connected to an applicant experience andattribute tracking database (“AEAT”) 150. AEAT 150 contains the externaldata used by ACM 110 in conjunction with the applicant responses toquestions presented in IIM 105 to characterize the applicant. In oneembodiment of the invention, AEAT 150 contains information relating tooffered and accepted products. This information may be periodicallyinvoked by Tracking Module 130 to generate a tracking report. Inaddition, information stored in the Applicant Experience and AttributeTracking Database AEAT 150 may be passed to the Learning Module 135.

The applicant's pool assigned in ACM 110 is then passed to: ProductOffers Module (“POM”) 115, i.e. Module 3; Complementary Product OffersModule (“CPOM”) 120; i.e. Module 4; and Offer Refinement Module (“ORM”)125; i.e. Module 5.

POM 115 evaluates the revolving credit products, based on a set ofattributes. Preferably, available revolving credit products are eachevaluated. The attributes on which the revolving credit productsevaluation is based may include, for example, the APR, interest rate,promotional APR, credit line, annual fees, reward points, color of acredit card, brand of a credit card, grace period for delinquentrepayment, repayment terms and fix/variable interest rate. Once theattributes are determined, POM 115 identifies the most appropriateproduct offers for each applicant based on each individual applicant'scharacteristics, as identified by the ACM 110, and the productattributes. This allows each applicant to be offered a relevant andunique experience.

In one embodiment of the invention, POM 115 obtains product codes (i.e.,numerical values describing each unique product offering) for theproducts from a table of product codes 116, and matches them with theissuer's objectives for the product, the objectives are stored in anobjectives table 117. The issuer's objectives may include objectivepriorities such as account growth, asset growth, risk and profit. Theproduct codes that meet the issuer's objectives are then matched withspecific descriptions and graphic presentation material from productpresentation table 118 to enhance the applicant's sales experience.

CPOM 120 may evaluate complementary products available to the applicantand identifies the most appropriate complementary product offers foreach applicant based on each individual applicant's characteristics asidentified by the ACM 110. Similar to Module 3 described above, CPOM 120obtains complementary product codes for the complementary products froma table of vendor complementary product codes 121, and matches them withthe issuer's objectives stored in an objectives table 117. Thecomplementary product codes that meet the issuer's objectives can bematched with specific descriptions and graphic presentation materialfrom a complementary product presentation table 122 to enhance theapplicant's sales experience.

In a preferred embodiment ORM 125 performs two functions. First, ORM 125may be used in connection with an existing customer seeking amodification to the issuer's credit card. In that case, ORM 125identifies alternative refinements that are acceptable to the issuer,and that may more closely align with the customer's needs. Secondly, ORM125 may be used in connection with applicants that are seeking a newrevolving credit product, and who have rejected the offers presented inPOM 115. In the latter case, ORM 125 allows the issuer to make severalproduct counter-offers that are equally acceptable to the issuer, andthat may more closely align with the applicant's needs. In oneembodiment of the invention, ORM 125 obtains refined product andcomplementary product codes for the products from tables of productcodes 116 and vendor complementary product codes 121, and matches themwith the issuer's objectives stored in an objectives table 117. Therefined product codes and complementary product codes that meet theissuer's objectives are then matched with specific descriptions andgraphic presentation material from tables 118 and 122 to enhance theapplicant's sales experience.

Modules IIM 105, POM 115, CPOM 120 and ORM 125 are all operativelyconnected to the Tracking Module 130, i.e, Module 6, through theapplicant experience and attribute tracking database AEAT 150. TrackingModule 130 is also operatively connected to the issuer's analyticdatabase 160, where individual customer's behavior and current producttypes and attributes are saved. Tracking module 130 reports the resultsof the applicant's experience and product attributes from these modulesin a consistent and reliable manner. To maintain consistency, TrackingModule 130 contains a reporting engine and a set of report templates tofacilitate the production and distribution of the tracking report. Thereport templates may summarize various results, including, for example,customer behavior, account profitability, sales performance etc.

Learning Module 135 leverages the experience of applicants andcustomers, as characterized by the applicants experience and attributetracking database AEAT 150 and issuer's analytic database 160, to learnin one or more distinct domains. In one embodiment of the invention, theLearning Module 135 learns how to align offers and counter offers toapplicants and customer. In another embodiment of the invention, theLearning Module 135 learns how to aggregate applicants in morehomogeneous and relevant groups to anticipate performance. In yetanother embodiment of the invention, the Learning Module 135 learns howto assess credit risk among thin-file applicants. In still a furtherembodiment of the invention, the Learning Module 135 learns in acombination of the domains.

In practice, the Learning Module 135 reads the applicant experience andattribute tracking database AEAT 150 and the issuer's analytic database160. In particular, the Learning Module reads the customer's behaviorinformation, as well as the applicant's responses to questions posed inmodules IIM 105, POM 115, CPOM 120 and ORM 125. This data is then usedto enhance the alignment of offers to applicants and credit riskevaluation among thin-file applicants. Learning will be reintegratedinto modules IIM 105, ACM 110, POM 115, CPOM 120 and ORM 125.

An overview of the method according to one embodiment of the presentinvention is shown in FIG. 2. In step 200, an identifier for each of aplurality of revolving credit products is stored. Each identifier can beused to uniquely identify a revolving credit product. At least oneattribute is associated with each of the revolving credit products asshown in step 205. As described earlier, these attributes may include,for example, the APR, interest rate, promotional APR, credit line,annual fees, reward points, color of a credit card, brand of a creditcard, grace period for delinquent repayment, repayment terms,fix/variable interest rate, etc. In one embodiment of the invention, theidentifiers and attributes are stored in a table of product codes.

An application for a revolving credit product is received from anapplicant as shown in step 210. In one embodiment of the invention, anapplicant accesses the revolving credit product issuer's web site, andthe applicant is presented with some initial screening questions. Aspreviously described, the initial questions may be used to determinewhether the applicant is a prospective or current customer, and if acurrent customer, whether the applicant is interested in modifying theattributes of an existing revolving credit product account, or isinterested in acquiring a new or alternative revolving credit productaccount. Once these initial questions have been answered, the systempasses the URL and applicant's needs gleaned from the questions to theIIM 105. If the applicant is also a current customer, the system alsoprovides information relating to the customer to the initial inputmodule (JIM 105). The IIM 105 presents a selection of questions to theapplicant designed to build on each other in order to clarify thecharacteristics of each applicant.

At step 215 the application is profiled to provide an applicationprofile. In one embodiment of the invention, as described above, theapplicant is characterized according to four objectives: riskassessment; behavior pattern; value assessment; and likelihood ofacceptance. The four objectives used to describe the applicant are usedto assign the applicant to a pool of applicants with similarcharacteristics.

In one embodiment of the invention, the results of the questionspresented to the applicant by the IIM 105 are then passed to theApplicant Characterization Module ACM 110. The ACM 110 uses the results,along with data extracted from the Applicant Experience and AttributeTracking Database AEAT 150 to assign the applicant to the appropriateand relevant pool. The applicant's assigned pool is then passed to theProduct Offers Module POM 115, the Complementary Product Offers ModuleCPOM 120, and the Offer Refinement Module OFM 125.

One or more of the revolving credit product issuer's objectives of theoffer are identified in step 220. In one embodiment of the invention,this involves determining the relative importance of key objectives ofthe issuer, for example, account growth, asset growth, risk and profit.From these key objectives, the issuer's objectives of the offer may bedetermined by using models that estimate the outcome of offering eachproduct to each group of customers for each objective (i.e., accountgeneration, asset generation, profit generation, credit losses, etc.).The relative importance of the issuer's objectives is passed to POM 115,CPOM 120 and OFM 125 from the issuer's objectives table 117.

In step 225, a set of revolving credit products (i.e. revolving creditproducts and complementary products) that fit within the applicant'sprofile is created. As described above, the revolving credit productsare described using the product codes or product attributes. In oneembodiment of the invention, the product is described using a pluralityof attributes stored in a table of product attributes.

The revolving credit products and complementary products are then rankedbased upon the issuer's objective of the offer, and the at least oneattribute of the revolving credit products as shown in step 230. In oneembodiment of the invention, the revolving credit products andcomplementary credit products are evaluated and prioritized by theproducts offers module POM 115 and complementary product offers moduleCPOM 120 respectively. As described earlier, in one embodiment of theinvention, POM 115 receives a list of the product codes for the productsto offer each applicant from the data table of product codes 116. Theproduct codes are matched and prioritized with the issuer's objectivesstored in objectives table 117. Similarly, CPOM 120 receives a list ofthe complementary products codes for the complementary products to offereach applicant from data table of complementary product codes 121. Inone embodiment of the invention, the complementary product codes arematched and prioritized with the issuer's objectives stored inobjectives table 117, the pool information from ACM 110, and informationpassed from the Learning Module 135 to determine the product offers tobe presented to the applicant. Once matched these product andcomplementary products are offered to the applicant as shown in step235.

A determination is then made as to the applicant's acceptance of theproduct and/or complementary product offer in steps 240. If an applicantaccepts an offer, the system exits at step 245 so that the offer can beprocessed. If, on the other hand, the offer is rejected, the offer isrefined as shown in step 250. The offer is then offered to the applicantas shown in step 255.

A determination is then made in step 260 as to the applicant'sacceptance or rejection of the refined offer. If the applicant acceptsthe refined product and complementary product offer, the system exits atstep 245 so that the offer can be processed. Alternatively, if theapplicant rejects the refined offer, the system exits at step 265.

In one embodiment of the invention, the Offer Refinement Module ORM 125is invoked to refine the offer.

FIG. 3 is a flow chart depicting the steps taken to determine thecharacteristics of each applicant in the Initial Input Module IIM 105(Module 1) according to one embodiment of the present invention. Basedon the applicant's characteristics and the referring URL, module IIM 105has a series of questions to present to the applicant. As describedearlier, these questions are designed to build on each other. In oneembodiment of the invention, the questions are selected so that based onthe responses to previous questions, further questions are presented tothe applicant. As applicants progress through the question trees, theapplicant's credit needs and values may be determined. In addition, forthin-file applicants, IIM 105 enables revolving credit productevaluation for those applicants who would not otherwise qualify forcredit based on available credit bureau files.

The applicant enters the module at step 300, and the referring URL alongwith external data is passed to IIM 105. In one embodiment of theinvention, the external data may comprise the applicant's unique ID,previous experience of applicants, and attribute data from AEAT 150. Aninitial question is presented at step 310. This question is selectedbased on information passed from the front-end questions in step 210,along with information extracted from the Applicant Experience andAttribute Tracking Database AEAT 150. A determination is made in step320 as to whether the question presented to the applicant is the lastquestion in the queue. If the answer to this query is in the negative,follow-up questions are selected and presented to the applicant at step330. In one embodiment of the invention, these follow-up questions arebased, at least in part, on the applicant's responses to the previousquestions. If the determination at step 320 is in the affirmative, thelast question is reached, at which point the module exits at step 340.The responses (and other available data) provide the basis for profilingeach applicant. Thus, as applicants progress through the question tree,the applicant's revolving credit product needs and values can bedetermined.

In addition, the questions presented to each applicant along with theapplicant's responses are stored in the Applicant Experience andAttribute Tracking Database AEAT 150 at step 350. The applicant'scharacteristics provided by the AEAT 150 are maintained by the issuer.

If the applicant is a current customer who is interested in acquiring anew or alternative revolving credit product, the front-end question atstep 210 will also pass information relating to the customer's needs tomodule IIM 105. At step 310, IIM 105 utilizes this information topresent an initial question to the applicant.

If a current customer is interested in modifying the attributes for anexisting revolving credit product, the system bypasses this modulealtogether, proceeding directly to the Applicant Characterization ModuleACM 110, described below.

FIG. 4 is a flow chart depicting the steps taken by the ApplicantCharacterization Module ACM 110 (Module 2) to characterize the applicantaccording to one embodiment of the present invention. This modulecharacterizes and profiles the applicant based on external data andresponses to questions presented in IIM 105.

At step 410, ACM 110 assigns each applicant to a characterization pool.In one embodiment of the invention, the applicant characterizationreflects the values, credit risk, potential profitability, and currentbehavior of each applicant (if the applicant is a current customer).These assignments are based on applicant responses and external dataextracted from the Applicant Experience and Attribute Tracking DatabaseAEAT 150 as described earlier. These characterization pools arefundamental to the offers to be made to each applicant.

Once each applicant has been assigned to a characterization pool, ACM110 determines, at step 420, whether the customer is modifying arevolving credit product attribute, or is seeking a new revolving creditproduct. If the response to this query is in the negative, thecharacterization pool is then passed on to the Product Offering ModulePOM 115, the Complimentary Product Offer Module CPOM 120, and the OfferRefinement Module ORM 125 as shown in step 430. If, on the other hand,the response to the query is in the affirmative, the characterizationpool is passed on to the Product Offering Module POM 115 and theComplimentary Product Offer Module CPOM 120 as shown in step 440. Thesesubsequent modules present the product offers, complementary products,and attribute trade-offs.

FIG. 5 is a flow chart depicting the steps taken by the Products OffersModule POM 115 (Module 3) to evaluate the products available, andidentify the most appropriate product offers for each applicant,according to one embodiment of the present invention. All products areevaluated and prioritized in relation to the applicant's characteristicsand issuer's objectives. Based on this evaluation, the top offers arepresented to the applicant in terms consistent with the applicationsystem.

The applicant characterization pool information from ACM 110 is passedto POM 115 at step 500. In one embodiment of the invention, thisinformation reflects the applicant's needs and values, credit risk,potential profitability, and current behavior as described earlier.

At step 510, the products available are evaluated, i.e., ranked, by POM115 for “appropriateness” with respect to an applicant. This permitsready identification of the most appropriate (i.e., highest ranking)offers for an applicant. In one embodiment of the invention, the POM 115receives product codes for the products to offer from the products codes116, and matches these products codes to the issuer's objectives inobjective table 117 to determine a set of potential product codes tooffer the applicant. POM 115 then identifies the most appropriateproduct offers for each applicant based on each individual applicant'scharacteristics (characterization pool), as identified by the ApplicantCharacterization Module ACM 110, and the issuer's objectives, derivedfrom objectives table 117.

Based on the ranking made in step 510, the top offers for an applicantare identified. The top offers are then presented to the applicant atstep 520. Preferably, to enhance an applicant's sales experience, thetop product offers are first matched with specific descriptions andgraphic presentation material from the product presentation table 122,and those graphics and text are used to present the offer. This matchingmay be completed prior to the product offer being made to the applicant,as, for example, in step 510, but is preferably performed in combinationwith the presentation of the offer to the applicant in step 520.

Thus, module POM 115 enables the revolving credit product issuers tooffer each applicant a relevant and unique experience. The issuers alsoreceive the list of product codes for the product offers made to eachapplicant.

If an applicant accepts an offer at step 530, POM 115 exits at step 540so that the offer may be processed. If, on the other hand, an applicantdeclines an offer at step 530, the applicant is asked which revolvingcredit product (or attribute) is closest to their desired revolvingcredit product, and which attributes needs to be improved at step 550.The applicant is then transferred to the Offer Refinement Module ORM 125at step 560. Module POM 115 also stores the codes for all productsoffered and for all product offers accepted in the Applicant Experienceand Attribute Tracking Database AEAT 150 at steps 570 and 580respectively.

FIG. 6 is a flow chart depicting the steps taken by the ComplementaryProduct Offers Module CPOM 120 (Module 4) to evaluate the complementaryproducts available, and identify the most appropriate complementaryproduct offers for each applicant, according to one embodiment of thepresent invention. Complementary products are evaluated and prioritizedin relation to the applicant's characteristics and issuer's objectives.Based on this evaluation, the top complimentary product offers arepresented to the applicant in terms consistent with complementaryproduct systems.

The applicant characterization pool information from ACM 110 is passedto CPOM 120 at step 600. In one embodiment of the invention, thisinformation reflects the applicant's needs and values, credit risk,potential profitability, and current behavior.

At step 610, the complimentary products available are evaluated, i.e.ranked, by CPOM 120 for “appropriateness” with respect to the applicant.This permits ready identification of the most appropriate (i.e. highestranking) complimentary offer for an applicant. In one embodiment of theinvention, the CPOM 120 receives complimentary product codes for thecomplimentary product offers from vendor complimentary products table121. These complimentary product codes are then matches to the issuer'sobjectives in objective table 117 to determine a set of potentialcomplimentary product codes to offer the applicant. CPOM 120 thenidentifies the most appropriate complimentary product offers for eachapplicant based on each individual applicant's characteristics(characterization pool), as identified by ACM 110, and the issuer'sobjectives derived from objectives table 117.

Based on the ranking made in step 610, the top complimentary offers areidentified. The offers are then presented to the applicant at step 620.Preferably, to enhance the applicant's sales experience, the topcomplimentary product offers are first matched with specificdescriptions and graphic presentation material from the complementaryproduct presentation table 122, and those graphic and text are used topresent the offer. This matching may be completed in step 610 prior tothe complementary offer being presented to the applicant, as forexample, in step 610, but is preferably performed in combination withpresentation of the offer to the applicant in step 620.

The complementary product offers are then presented to the applicant byCPOM 120 at step 620. If an applicant accepts an offer at step 630,module CPOM 120 exits at step 640 so that the complementary productoffer may be processed. If, on the other hand, the applicant declinesthe offer at step 630, the module CPOM 120 may take several differentpaths. In one embodiment of the invention, the module CPOM 120 may exitat step 640. Alternatively, in another embodiment of the invention, theapplicant can be transferred to the Offer Refinement Module ORM 125 atstep 650 so that an offer more closely aligned with the applicant'sneeds can be identified.

Module CPOM 120 also stores the codes for all complementary productsoffered (in step 620), and for all complementary product offers accepted(in step 630), in database AEAT 150 at steps 660 and 670 respectively.

FIG. 7 is a flow chart depicting the steps taken by the Offer RefinementModule ORM 125 (Module 5) to refine offers made to existing andprospective customers according to one embodiment of the presentinvention. This module performs two functions. First, for existingrevolving credit product customers who identified in module IIM 105 thatthey are seeking a modification to their revolving credit product,module ORM 125 identified alternative refinements that are acceptable tothe issuer and that more closely align with the customer's needs.Second, for those applicants who are seeking a new revolving creditproduct, and who have rejected the offers presented in module POM 115 orCPOM 120, module ORM 125 allows the applicant to make several productcounter-offers that are equally acceptable to the issuer and that moreclosely align with the customer's needs.

In either scenario, module ORM 125 determines a set of feasiblerefinement offers to enable the issuer to offer each applicant anotheropportunity to find a product that meets his or her needs. Thisrefinement offer is determined in step 720.

In one embodiment of the invention, the issuer receives the list ofproduct or complimentary product codes reflecting the refinement offersto be made from module POM 115 and CPOM 120, steps 700 and 710respectively. These codes may represent products in the products table116 and/or vendor complimentary product codes table 121 that were notinitially offered to the applicant. In another embodiment of theinvention, these codes may represent products in the products table 116and/or vendor complimentary product codes table 121 that the applicanthas identified (from among the rejected offer list) as being closest toan offer they would likely accept. Applicants are then asked whichproduct and/or complimentary product attribute would need to be modifiedfor them to accept the offer.

In one embodiment of the invention, the product codes are matched to theissuer's objectives in objective table 117 to determine a set ofpotential product codes to offer the applicant. ORM 125 then identifiesthe most appropriate product offers for each applicant based on eachindividual applicant's characteristics (characterization pool), asidentified by ACM 110, and the issuer's objectives derived fromobjectives table 117.

Based on this evaluation, the top refined product offers are completeand ready for presentation to the applicant as shown in step 720.Preferably, to enhance the applicant's sales experience, the refinementproduct codes are matched to specific descriptions and graphicpresentation material and presented to the applicant at step 730, sothat the applicant can interact with the issuer's trade-off selections.

A determination is made in step 740 as to the applicant's acquiescencein the refined offer. If the refined offer is accepted by the applicant,the applicant is transferred to step 540 (for product codes) or 640 (forcomplimentary product codes) so that the offer can be processed. If therefined offer is declined by the applicant, the module exits at step750. In this case, no sale is made. In addition, the product codes forthe accepted offer are stored in the Applicant Experience and AttributeTracking Database 150 as shown in step 760.

FIG. 8 is a flow chart depicting the steps taken by the PerformanceTracking Module 130 (Module 6) to create a set of management reportsaccording to one embodiment of the invention. In one embodiment of theinvention, management report templates detail the applicant behavior,account profitability and sales performance, and loads them into areporting engine.

The report engine is operatively connected to Tracking Module 130. Thereports are designed to summarize data included in the applicantexperience and attribute tracking database AEAT 150 and the issuer'sanalytic database 160. The report engine enables fast production anddistribution of performance measures in a consistent and reliable mannerwith a limited need for ad hoc reporting.

In order to generate these reports, the report engine obtainsinformation regarding the applicants' experience as shown in step 800.In one embodiment of the invention, this data is obtained from theApplicant Experience and Attribute Tracking Database AEAT 150, andincludes information regarding questions presented to each applicant andtheir responses, and product codes for all products, includingcomplementary products, that were offered to applicants, and all productcodes for those offers that were adapted by applicants. This informationmay be supplied to AEAT 150 by IIM 105, POM 115, CPOM 120 and ORM 125 asdescribed earlier.

Similarly, the report engine also utilizes customer behavior informationgathered in step 810 when generating the reports. In one embodiment ofthe invention, this information is obtained from the issuer's AnalyticDatabase 160.

Tracking Module 130 reports results in a consistent and reliable manner.A set of report templates are designed and programmed to summarizecustomer behavior, account profitability, sales performance, etc. Thereport templates detailing the applicant's behavior, profitability andsales performance are created and loaded into a report engine, and areport is generated, as shown in step 820. once the report is prepared,the module exits as shown in step 830. The report engine facilitatesmass production and distribution of these reports in a consistentmanner.

FIG. 9 is a flow chart depicting the steps taken by the Learning Module135 (Module 7) to leverages the experience of applicants and customersaccording to one embodiment of the present invention.

Learning Module 135 leverages the experience of applicants and customersas characterized by the Applicant Experience and Attribute TrackingDatabase AEAT 150 and the issuer's Analytic Database 160, to learn inthree distinct domains. First, Learning Module 135 learns how to alignoffers and counter offers to applicants and customers. Second, LearningModule 135 learns how to aggregate applicants in more homogeneous andrelevant groups or pools to anticipate performance. Finally, LearningModule 135 learns how to assess credit risk among thin-file applicants.

The Learning Module 135 accesses the Applicant Experience and AttributeTracking Database AEAT 150 and the issuer's Analytic Database 160 tosupport ongoing learning and analysis. The module then evaluatesapplicants' responses and the behavior associated with accepted andrejected offers to understand how to align products to meet the issuer'sobjectives. The evaluation of offers in this format is similar to ahybrid conjoint analysis. Applicant Experience and Attribute TrackingDatabase AEAT 150 is particularly rich in its ability to support thisgoal in so far as applicants are presented with several offers throughModules POM 115, CPOM 120 and ORM 125. Thus, the Learning Module enablesthe invention to improve the targeting of offers to applicants throughthe refinement of the pools as well as the targeting of offers to pools.

In one embodiment of the invention, the module is implemented as acomputer program that reads the Applicant Experience and AttributeTracking Database AEAT 150 and the issuer's Analytic Database 160 asshown in steps 900 and 910 respectively. These data are used to enhancethe alignment of offers to applicants and credit risk evaluation amongthin-file applicants. Learning is reintegrated into Modules IIM 105, ACM110, POM 115, CPOM 120 and ORM 125.

In order to determine better aligned offers to meet the objectives foreach pool, Learning Module 135, at step 920, analyzes issuer'sobjectives and applicants' responses and the behavior associated withaccepted and rejected offers. The responses are taken from responses toModules IIM 105, POM 115, CPOM 120 and ORM 125, as stored in theApplicant Experience and Attribute Tracking Database AEAT 150. Customerbehavior information is obtained from the issuer's Analytic Database160. The improved offers are presented to Modules POM 115, CPOM 120 andORM 125 at step 950.

In order to improve the questions presented to applicants, as well as toimprove the applicant characterization pools, the Learning Module 135,at step 930, analyzes questions presented and applicants' responses. Thequestions and responses are those saved by Module JIM 105 in theApplicant Experience and Attribute Tracking Database AEAT 150. Theimproved questions and characterization pools are presented to ModulesIIM 105 and ACM 110 at step 960.

For thin-file applicants and non-traditional credit seekers, theLearning Module 135 analyses questions and responses from Module IIM 105along with associated customer behavior at step 940, so that the systemcan develop an alternative battery of questions and risk evaluationsassociated with alternative responses. The module utilizes responsesfrom questions presented in Module IIM 105 saved in the ApplicantExperience and Attribute Tracking Database AEAT 150, and customerbehavior information extracted from the Analytic Database 160. Theseimproved questions and offers are presented to Modules IIM 105, POM 115,CPOM 120 and ORM 125 at step 970.

The present invention is in no way limited to the embodiment describedabove. It will be immediately apparent to those skilled in the art thatvariations and modifications to the disclosed embodiment are possiblewithout departing from the spirit and scope of the present invention.The invention is defined by the appended claims.

1. Method of making an offer for revolving credit products to anapplicant, the method comprising the steps of: a. Storing an identifierfor each of a plurality of revolving credit products; b. Associating atleast one attribute with each of the revolving credit products; c.Receiving an application from an applicant; d. Profiling the applicationto provide an applicant profile; e. Identifying an objective of theoffer; f. Creating a set of revolving credit products, the setcomprising a plurality of revolving credit products that fit within theapplicant profile; g. Ranking the set of revolving credit products basedupon the objective of the offer and the at least one attribute of eachrevolving credit product in the set; and h. Offering to the applicant atleast one of the top ranking revolving credit products from the set ofrevolving credit products.
 2. The method of claim 1 where the step ofprofiling the application comprises obtaining a set of objective indiciadescribing the application based on the application received from theapplicant.
 3. The method of claim 2 wherein the set of objective indiciadescribing the application comprises assessing the applicant's risk,value, and behavior.
 4. The method of claim 3 wherein assessing theapplicant's risk comprises the step of obtaining a numerical value. 5.The method of claim 3 wherein assessing the applicant's risk comprisesthe step of obtaining a FICO number.
 6. The method of claim 3 whereinassessing the value comprises the steps of: a. obtaining informationfrom an applicant; b. evaluating the information obtained from theapplicant based on historical data of similar applicants; and c.assigning a value assessment tag to the applicant based on theinformation obtained.
 7. The method of claim 3 wherein assessing thevalue comprises the step of categorizing an applicant based upon theapplicant's known characteristics.
 8. The method of claim 3 whereinassessing the applicant's behavior comprises the steps of: a. obtaininginformation from an applicant; b. evaluating the information obtainedfrom the applicant based on historical data of similar applicants; andc. assigning a value to the applicant's behavior based on theinformation obtained.
 9. The method of claim 3 wherein the assessment ofbehavior comprises the steps of: a. evaluating one or more behaviorpatters of an applicant; and b. determining one or more numerical valuesdescribing the applicant's behavior patterns.
 10. The method of claim 3wherein profiling the application comprises the step of obtaining acredit profile for the applicant.
 11. The method of claim 1, whereinidentifying an objective of the offer comprises performing a relativevaluation between a plurality of sub-objectives.
 12. The method of claim11 wherein performing a relative valuation between sub-objectivescomprises valuating risk and profit.
 13. The method of claim 11 whereinperforming a relative valuation between sub-objectives comprisesvaluating risk, profit, size and accounts.
 14. The method of claim 1wherein the step of receiving an application from an applicant comprisesthe steps of: a. generating a first set of questions, the questionsrelating to the demographics of the applicant; b. presenting theapplicant with the first set of questions, and determining demographicinformation on the basis of a first set of responses thereto; c.generating a second set of questions, the second set of questionsrelating to product desires of the applicant; and d. presenting theapplicant with the second set of questions, and receiving a second setof responses thereto.
 15. The method of claim 14 wherein the step ofgenerating a second set of questions comprises taking prior questionsand responses and identifying the next question to present to theapplicant based on the prior question.
 16. The method of claim 1 whereinthe step of creating a set of revolving credit products comprisesevaluating the attributes of the revolving credit products in relationto the objectives of the offer.
 17. The method of claim 1 wherein thestep of ranking the set of revolving credit products comprisesevaluating the set of revolving credit products based upon at least theobjectives of the offer and the attributes of the revolving creditproducts.
 18. The method of claim 1 further comprising the step ofrefining the offer to the applicant if the applicant rejects at leastone of the top ranking revolving credit products from the set ofrevolving credit products.
 19. The method of claim 18 wherein the stepof refining the offer to the applicant comprises the steps of: a.determining attributes of the revolving credit product that more closelyaligns with the applicant's needs; b. creating a refined set ofrevolving credit products, the refined set of credit products beingbased upon a plurality of revolving credit products that more closelyalign with the applicant's needs; c. ranking the set of refinedrevolving credit products based upon the objectives of the offer and theattributes of the revolving credit products that more closely align withthe applicant's needs; and d. offering at lease one of the top rankingrefined revolving credit products from the set of refined revolvingcredit products to the applicant.
 20. A system for making an offer forrevolving credit products to an applicant, the system comprising: a. aninitial input module, the initial input module presenting questions toan applicant and soliciting responses from the applicant; b. anapplicant characterization module, the applicant characterization moduleprofiling the applicants based on the responses to questions presentedby the initial input module; c. a product offers module, the productoffers module creating and presenting a set of revolving credit productsto the applicant based on the applicant's profile and objectives of theoffer; d. a complementary product module, the complementary productmodule creating and presenting a set of complementary products to theapplicant based on the applicant's profile and objectives of the offer;21. The system of claim 20 further comprising: a. an offer refinementmodule, the offer refinement module capable of refining revolving creditproduct and the complementary product offers to the applicant.
 22. Thesystem of claim 20 further comprising: a. a performance tracking module,the performance tracking module being capable of generating reports. 23.The system of claim 20 further comprising: a. a learning module, thelearning module being capable of evaluating the applicant's responsesand behavior associated the revolving credit product offers andcomplementary product offers.